Evaluating performance of denoising algorithms using metrics : MSE,MAE,SNR,PSNR & cross correlation

This code computes the metrics MSE, MAE, SNR, PSNR and cross correlation coefficient .
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Updated 12 Oct 2015

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This function is useful in evaluating the performance of denoising algorithms, such as ECG, EEG, audio (speech) etc. I have attached a demo script, which you can use to run to understand its use.
Please contact me if you have doubt in using this code

Cite As

Aditya Sundar (2024). Evaluating performance of denoising algorithms using metrics : MSE,MAE,SNR,PSNR & cross correlation (https://www.mathworks.com/matlabcentral/fileexchange/52342-evaluating-performance-of-denoising-algorithms-using-metrics-mse-mae-snr-psnr-cross-correlation), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2014a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Evaluate performance of denoising algorithms/

Version Published Release Notes
1.0.0.0

The initial version did'nt contain some important files
Updated comments and demo script. This should be useful to beginners in study of signal denoising and performance evaluation techniques.

Updated some comments and demo script